科系選擇與兩性薪資差異 = Gender Wage Gap and Ch...
國立高雄大學應用經濟學系碩士班

 

  • 科系選擇與兩性薪資差異 = Gender Wage Gap and Choices of Major
  • 紀錄類型: 書目-語言資料,印刷品 : 單行本
    並列題名: Gender Wage Gap and Choices of Major
    作者: 莊佳芸,
    其他團體作者: 國立高雄大學
    出版地: [高雄市]
    出版者: 撰者;
    出版年: 2015[民104]
    面頁冊數: 72面圖,表格 : 30公分;
    標題: 兩性薪資差異
    標題: Gender Wage Gap
    電子資源: http://hdl.handle.net/11296/ndltd/98358476631651777758
    附註: 106年10月31日公開
    附註: 參考書目:葉66-68
    附註: 含附錄
    摘要註: 歷年來兩性薪資存在明顯的差異,處於男性薪資高於女性情形,而台灣女性薪資占男性薪資的比例自1978的67.5%提高至2013的82.5%,顯示兩性薪資差異有逐漸下降的趨勢,但此差異仍然存在。然而,隨著大學教育的普及,了解教育程度的差異以及科系的選擇對兩性薪資差異的影響為何,是一個值得去討論的議題。本文利用1978年至2013年行政院主計總處所提供的「人力資源附帶專案調查-人力運用調查」來探討不同科系之兩性薪資差異。我們首先探討各科系性別比例、各科系性別薪資差異以及產業、職業兩者與科系是否有相關,初步發現不同性別有不同的科系選擇偏好,進而影響了未來職場上的產業及職業,可能造成兩性薪資差異,因此了解科系選擇有其重要性。然而,根據本文實證模型結果,大部分科系皆存在男性薪資高於女性的情況,我們利用Oaxaca薪資分解方程式了解各科系薪資差異來源,觀察個人特徵差異(可解釋)及歧視(無法解釋)影響差異的比例。實證結果發現,1978-2013年男性薪資平均高出女性29.3%,而形成差距原因主要來自無法解釋的歧視差異,約占總差距的75.5%~81%,可解釋的個人稟賦差異約占總差距的18.8%~24.5%。在控制高職以上學歷的情況下,兩性薪資差距最大的科系為商管及醫科,其餘科系薪資差異由大到小依序為農、工、軍警、理、法、文,最小者為教育,而各科系兩性薪資差異原因於可以解釋以及無法解釋比例上,商、管理科系可解釋部分占兩性薪資差異的45.4%,工科之可解釋部分占兩性薪資差異的30.6%。最後,我們探討模型的解釋能力,發現學歷越高兩性薪資差異越小,且可解釋部分越高,而模型在控制產業及職業虛擬變數後,加入科系虛擬變數仍可使模型解釋能力上升,顯示科系對於解釋兩性薪資差異有其重要性。然而,科系對於兩性薪資差異影響在1978-1989年間較為重要,而2002-2013年間轉變成產業及職業對於兩性薪資差異的影響較為重要,隨時間的改變,科系的重要性有逐漸遞減的現象。 Over the past few decades, the wage of male workers is always higher than that female in the labor market. The wage of female was only about 67.5% of those of males in 1978, and it increased to 82.5% in 2013. Although the gender wage gap tended to shrink over time, the differences between male and female still exist. The main purpose of this thesis is to investigate the relationship between gender wage gap and choices of major. Firstly, we use 1978-2013 Manpower Utilization Survey and analyze the gender differences in both of majors and wage gaps. The observed data seems indicate that the gender preference of choices in majors is correlated with gender wage gaps. Then, we apply the standard Oaxaca decomposition to investigate the wage gap between male and female workers. The estimated results show that the average wage of male is 29.3% higher than female from 1978 to 2013. Most of differences in gender wage gaps are caused by the unexplained component which stands around 75.5% to 81%. For workers with senior occupational high school education and above, the size of gender wage gaps are in descending order as follows: Business, Medicine, Agriculture, Engineering, Police, Science, Law, Literature and Education. Our empirical results also show that the higher the workers' education, the less the proportion of the differences in wage gap cannot be explained by gender differences in endowment. Finally, after controlling for industry and occupation, choices of major still can enhance the explaining power of the model, which indicates that choices of major play an important role in explaining gender wage gaps. However, the importance of majors in explaining the gender wage gaps has decreased over times.
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